International Journal of Critical Infrastructure Protection最新文献

The cyber domain has led to growth in current satellite capabilities, which have become essential due to the increased use of both civil and military critical infrastructure (CI) management systems. In recent decades, outer space has proven to be an increasingly critical sector for the international management of commercial CI, with private operators acting on both multi- and transnational levels. However, the space domain is characterised by not only opportunities but also risks and threats. As the security implications of space were not sufficiently considered at the beginning of the space era, some of the predominant risks currently extend into the commercial sphere. These risks must be considered to ensure the resilience of connected CIs in outer space. Security is a vital issue in the cyber and space domains and should be considered in every phase of a space system's life cycle, from the development and manufacturing of space assets to their deployment and end of life. This involves CI in several sectors, each of which exhibits different but interrelated risks. For example, telecommunications and location systems increasingly require the use of CI, which creates a fragile interdependence that is extremely vulnerable to threats. This paper underlines the importance of recognising space systems as CI and emphasises the need for a better integration of these assets in a system-of-systems analysis. The consequences of global satellite disruption on terrestrial CI are used to support this view. In such a disruptive scenario, mitigation measures based on in-orbit servicing or responsive space capabilities, for example, would allow CI to be restored to first ensure national security followed by commercial activities. Moreover, this paper provides an overview of the legal and policy aspects of using space systems’ capabilities in CI to better understand their implications and encourage the development of recommendations.

This paper comprehensively reviews the challenges posed by cybersecurity and cyber-terrorism to energy-related infrastructures. The article highlights the difficulty in monitoring, managing, and measuring cybersecurity threats and discuss the critical need for analysis in this area, particularly in the energy sector, where control and command operations are conducted in an internetworked environment. Despite the energy industry's effective risk management practices, it remains vulnerable to cyber-terrorism, as evidenced by the Stuxnet attack. This hardware-software co-designed mechanism targeted Iranian nuclear facilities. The authors explore the technical aspects of Stuxnet and its impact on the energy sector, emphasising the need for proactive measures to mitigate the risks posed by cyber-terrorism. The economic implications of cyberattacks on energy infrastructures are also discussed, including the potential for significant financial losses and reputational damage. The authors provide practical guidance on preventive measures and defence mechanisms, such as network segmentation, access control, and encryption, to help prevent cyberattacks. In a nutshell, this paper serves as a timely and insightful reminder of the ongoing challenges faced by energy-related infrastructures in cybersecurity and cyber-terrorism. It underscores the need to continue developing effective risk management strategies and implementing appropriate measures to protect against cyber threats.

This study analyzes the mileage and incident data between 1995 and 2016 corresponding to the onshore oil and natural gas transmission pipelines regulated by the Canada Energy Regulator (CER) and Pipeline and Hazardous Materials Safety Administration (PHMSA) of the United States. The analysis indicates that the material/weld/equipment failure is the leading failure cause for both CER and PHMSA pipeline incidents. The annual average incident rates of the CER and PHMSA pipelines are in the order of 10⁻³ per km except for the PHMSA gas pipelines, the annual incident rate of which is in the order of 10⁻⁴ per km. The annual average rupture rates of the CER and PHMSA pipelines vary from 3.5 × 10⁻⁵ to 4.5 × 10⁻⁵ per km. The F-N curves for the PHMSA pipelines are developed based on the mileage and incident data to quantify the societal risks posed by the pipeline in general.

Industrial control systems (ICSs) are extensively utilized worldwide to control and regulate various processes in energy utilities. It consists of various field devices, control and monitoring devices and communication devices. This paper focuses on the testing and analysis of various attack vectors that could potentially occur in a hardware-in-loop (HIL) Industrial Control System (ICS) testbed designed for a 500 MW thermal power plant. In this testbed, four typical process scenarios have been identified that can be manipulated through cyber-attacks, leading to severe issues such as plant shutdown or even explosions. The four significant plant scenarios recognized include minimal coal mill levels and increased temperatures in the classifier, heightened primary airflow to the coal mill, the tripping of an ID fan, and adjustment of the Super-heater temperature to its lowest setting. Also, we utilize the STRIDE threat modeling methodology to accurately represents the elements of Cyber-Physical Systems (CPS), their inter-dependencies, and the potential attack entry points and system vulnerabilities.

The cyber-physical system (CPS) plays a crucial role in supporting critical infrastructure like water treatment facilities, gas stations, air conditioning components, and smart grids, which are essential to society. However, these systems are facing a growing susceptibility to a wide range of emerging attacks. Cyber-attacks against CPS have the potential to cause disruptions in the accurate sensing and actuation processes, resulting in significant harm to physical entities and posing concerns for the overall safety of society. Unlike common security measures like firewalls and encryption, which often aren't enough to deal with the unique problems that CPS architectures present, deploying machine learning-based intrusion detection systems (IDS) that are specifically made for CPS has become an important way to make them safer. The application of machine learning algorithms has been suggested as a means of mitigating cyber-attacks on CPS. However, the limited availability of labelled data pertaining to emerging attack techniques poses a significant challenge to the accurate detection of such attacks. In the given scenario, transfer learning emerges as a promising methodology for the detection of cyber-attacks, as it involves the implicit modelling of the system. In this research, we propose a new lightweight transfer learning method via ResNet50-CNN1D for intrusion detection in CPS. The Adaptive Gradient (Adagrad) optimizer was applied in the proposed model to minimize the loss function through the adjustment of network weight. We tested how well the suggested ResNet50-1D-CNN model worked using the UNSW-NB15 dataset and a control system dataset called HAI. The HAI dataset was taken from the testbed and based on a planned physical attack scenario. By calculating the coefficient scores for the top ten (10) features in the HAI and UNSW-NB15 data, it was possible to determine the relevance of a feature. The rationale behind employing transfer learning was to mitigate the complexity associated with the classification of cyber-attacks and runtime. The utilization of transfer learning resulted in notable reductions in both the training and testing times required for the detection of attacks. On the HAI data, the results showed an accuracy of 97.32 %, recall of 98.41 %, F1-score of 96.32 %, and precision of 97.09 %. On the UNSW-NB15 data, the results showed an accuracy of 99.89 %, recall of 99.09 %, F1-score of 98.01 %, and precision of 98.70 %.

During the post-disaster recovery process of the urban system (US), it is critical to understand the interdependencies of critical infrastructure systems (CISs) and strategically allocate resources among them. However, due to the complexity of the problem and the limitations of the perspective, the existing research usually ignores the implicit impact of interdependence and resource allocation on urban resilience. To bridge this gap, this study establishes a multilayer network-based methodological framework to characterize various types of interdependencies between different CISs and integrate the US as a complex “system of systems”. Then, the system functionality of the US under different resource allocation strategies is quantified and optimized by resilience metrics. This proposed framework was demonstrated in a virtual US including a transportation subsystem (TS), an electric power supply subsystem (EPSS), and a community subsystem (CS) under catastrophic earthquakes. The sensitivity of urban resilience to interdependencies is investigated, and the corresponding results reveal that urban resilience is most sensitive to the interdependence between TS and EPSS. In particular, when there exists strong interdependence between the TS and EPSS, the optimal resource allocation strategy to maximize urban resilience is assigning resource allocation coefficients of 0.1, 0.8, and 0.1 for the TS, EPSS, and CS, respectively. These results can be effectively applied in future planning and investment in urban resilience.

The distribution system is digitizing and occupying cyberspace with the help of information and communication technologies (ICTs). It is vulnerable to cyber-attacks like false data injection (FDI) and denial-of-services (DoS). However, limited research on cyber-attacks in the distribution system is reported in the literature, and these attacks are of serious concern to distribution system operators (DSOs). The DSO's primary challenge is to understand the attacker's perspective for FDI attack construction. Thus, the work presented in this paper aims to provide an in-depth insight for DSO to apprehend the attacker's perspective, attack flow, and the nature of the FDI attack vector. The prior knowledge of attack flow to DSO can help to protect critical infrastructures from cyber-attacks. Thus, this work comprehends the attacker's behaviour for deploying the optimal budget to disrupt the distribution system operation therein by injecting a stealthy FDI vector. The attacker is resource-constrained in terms of budget and network information. Therefore, the optimal budget for attack initiation is proposed and formulated as a multi-objective optimization problem to minimize the investment and maximize the economic loss for the DSO. Constructing the attack vectors for the attacker is challenging in the limited network information. It is complex because of network characteristics such as multi-phase configurations & an unbalanced nature, and higher resistance to reactance ($r/x$) ratio. Thus, the FDI attack vector construction is proposed based on non-linear programming optimization and sensitivity analysis considering partial information from the distribution system. The simulation results are presented and compared with available methods in the literature to validate the efficacy of the proposed methods.

Industrial Control Systems (ICS) security happens often, which makes it hard for many organizations to keep a balance between operational efficiency, system efficiency, and security. A major concern is how to protect information security and make sure that ICS keep working. This study thus presents a defense-based system with adaptive cyber resilience (DSACR). DSACR will optimize the configuration with respect to the three indices of operational efficiency, performance, and security. Whenever an assault event happens, DSACR offers protective solutions depending on the threat level to optimize the security and running costs of recovering ICS. In terms of safety and operation, DSACR is superior to other approaches by 3 % and 11 %, respectively, as shown by the results of the experiments.

The security of cyber–physical systems (CPS) presents new challenges stemming from computations that work primarily with live physics data. Although there is a body of previous research on detection of malware on CPS, more effective designs are needed to address limitations such mimicry attacks and other forms of evasive techniques. Relay algorithms in particular, such as differential and harmonic protection algorithms, are essential to protecting physical equipment such as power transformers from faults. Relay algorithms, though, are often disabled, altered, or otherwise suppressed by malware.

In this paper, we first provide background on the main types of failures that may occur in an electrical power substation after relay algorithms are disabled by malware. We also provide some initial insights into malware methods that involve physics-informed data manipulations, which in turn may lead to power outages and physical damage to power transformers. We then describe the design of a watchdog algorithm that is continuously on the look out for anomalies in the execution time of relay algorithms along with their associated performance counters. We implemented the watchdog approach in Python, and evaluated it empirically on emulations of differential and harmonic protection algorithms on a computing machine.

With an increasing demand for authenticated data exchange between jurisdictions, ensuring the privacy and security of data interactions is crucial for national security, public health, and economic vitality, becoming a fundamental national infrastructure. Current solutions can be categorized into two types: fully decentralized autonomous systems based on blockchains or centralized solutions that rely on authoritative centers such as certification authorities (CAs). In reality, a balance needs to be struck between guaranteed authority and privacy independence. A certain authority is needed as an authorization guarantee, and decentralization is required to ensure privacy and the independence of the authority. This paper proposes a novel scheme, CT-MA-ABE (Cross-Trust Multiple Authorization Attribute-Based Encryption), to address these issues by implementing MA-ABE for cross-border institutional authorization interactions, utilize blockchain certification authority (BCA) for credibility and encryption-based authorization to protect attribute data privacy. This solution integrates the role of 'notary' in cross-border interactions, addressing the supervision problem in fully decentralized approaches while also considering the trust issue in centralized systems. This paper also introduces the Universal Certificate Authority Pool (UCAP), an innovative hybrid federated authorization method, creatively utilizing the implied authorization conditions of attributes to create a flexible and transitive authorization mechanism based on attribute relationships and extensions, enhancing privacy protection and improving the speed of authorization matrix calculation. The successful deployment of the system between the legal jurisdictions in South China, Zhuhai and Macau as a critical infrastructure component for securing data interactions further demonstrates its effectiveness as a reliable and secure solution.